In recent years, the advent of deep learning (DL) has revolutionized various fields, including healthcare. This paper provides a review and analysis of machine learning (ML) and DL-based techniques for the detection and diagnosis of cardiovascular disease (CVDs), which are among the leading causes of mortality globally. There is an immediate need for research into the factors that affect CVD. This requires innovative techniques to detect the disease early on and help bring the death rate down. In this paper, the analysis has been done based on research work executed by researchers in the CVDs identification along with the inferences drawn from the review done.